N,N,N-trimethylchitosan-poly (n-butylcyanoacrylate) core-shell nanoparticles as a potential oral delivery system for acyclovir
Bibliographic record
Abstract
This study investigated the feasibility of polysaccharide-coated poly(n-butyl cyanoacrylate) (PBCA) nanoparticles for oral delivery of acyclovir (ACV). PBCA nanoparticles were obtained by the emulsion polymerization method. Chitosan was chemically modified to obtain N,N,N-trimethylchitosan (TMC), which was used to coat the nanoparticles (PBCA-TMC). Nanoparticles were characterized by dynamic light scattering, zeta potential, differential scanning calorimetry (DSC), atomic force microscopy (AFM), cytotoxicity, and the effect on the transepithelial electrical resistance (TEER) of the Caco-2 cells. The size of the coated nanoparticles (296.2 nm) was significantly larger than uncoated (175.0 nm). Furthermore, PBCA nanoparticles had a negative charge (-11.7 mV), which was inverted to highly positive values (+36.5 mV) after coating. DSC analysis suggested the occurrence of the coating, which was confirmed by AFM images. The MTT assay revealed concentration-dependent cytotoxicity for the core-shell nanoparticles. Additionally, PBCA-TMC caused a significant but reversible decrease in the Caco-2 cell monolayer TEER. Entrapped ACV (PBCA-ACV-TMC), a Biopharmaceutical Classification System class III drug substance, increased approximately 3.25 times the Papp of ACV in the Caco-2 permeability assay. The nanoparticles were also able to provide in vitro ACV controlled release using media with different pH values (1.2; 6.8; 7.4). Accordingly, this new core-shell nanoparticle showed the potential to improve the oral delivery of ACV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".